Quantification of polynucleotide analytes from dried samples

ABSTRACT

Presented are methods, systems, and software products useful for determining the concentration of an analyte in a fluid specimen used to produce a dried sample, where the dried sample serves as a source of the analyte in a detection and quantification procedure. Particularly illustrated is the use of dried blood spots for quantifying a polynucleotide analyte.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. § 119(e) of UnitedStates Provisional Application Nos. 62/946,270, filed Dec. 10, 2019, and62/945,685, filed Dec. 9, 2019. The entire disclosures of these earlierapplications are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to the field of biotechnology.More specifically, the disclosure concerns methods, systems, andsoftware products for determining the concentration of an analyte in aliquid specimen used for preparing a dried sample, where the driedsample serves as a source of the analyte in a detection andquantification procedure.

BACKGROUND

The use of dried bodily fluid samples, such as dried blood samples, foranalyte detection greatly expands the availability of sophisticatedlaboratory testing by simplifying the requirements for samplecollection, transport, and processing. A dried blood spot (DBS)represents a particular type of dried sample. More specifically, a DBSis a form of biosampling where 50-70 μl of blood is blotted onto acircle of filter paper, dried, and then used for detection of one ormore bioanalytes in the blood sample. By this approach, a blood spot canbe conveniently prepared, dried, and then sent to a remote testinglocation. The place where the blood sample is taken for spotting neednot have resources for performing conventional blood draws. Theadvantage here is that bioanalyte testing can be made available toresource-challenged environments, as well as to the anonymous donationand home testing categories.

The use of DBS sampling offers many advantages. For example, samples areeasy to collect, store, and transport without requiring refrigeration.Sample acquisition is less invasive than drawing blood by phlebotomy, asonly very small blood volumes are required. Dried samples can be stableat ambient temperature for months. Thus, this type of sample provides aconvenient way to offer laboratory access to patients outside thetraditional clinical setting. The dried sample can even be used as asource of templates for priming in vitro nucleic acid amplificationreactions, such as real-time nucleic acid amplification reactions.

Unfortunately, conversion of a quantitative DBS result (e.g., measuredin copies/ml using a reconstituted DBS sample) to an accurate “wetsample” result (e.g., measured in copies/ml) for a liquid or fluidsample of a different type (e.g., whole blood or plasma) can be verychallenging. Quantitative outputs from nucleic acid analyzers processingliquid samples (e.g., plasma samples) are typically very different fromquantitative outputs produced using reconstituted DBS samples. Indeed,efficiencies of sample preparation can differ significantly for directsampling of a fluid blood product and a reconstituted DBS sample,thereby affecting the quantity of native target entering the pathway foramplification and detection.

A close correspondence between the DBS and wet sample quantitativeresults can be critical if the DBS result is to be used for making aninformed decision regarding a medical treatment, or change in treatment.For example, if DBS test results are to be used for determining failureof an antiretroviral treatment for HIV-1, then according to World HealthOrganization guidelines (WHO Consolidated Guidelines on the use ofantiretroviral drugs for treating or preventing HIV infection, 2016) thetest must be capable of detecting when the HIV viral load exceeds alevel of 1,000 copies/ml in plasma.

The present disclosure addresses the need for converting results fromDBS testing to a wet sample standard, thereby relating the two resultsto each other in a manner that is both highly accurate and precise.

SUMMARY OF THE DISCLOSURE

Provided herein are the following embodiments.

Embodiment 1 is a method of quantifying a polynucleotide analyte presentin a fluid blood sample that dried to produce a dried blood spot (DBS),the method comprising the steps of: (a) performing a nucleic acidamplification reaction using the DBS as a source of templates to produceamplification products and obtain a measured result, the measured resultindicating a concentration or an amount of the polynucleotide analyte;and (b) multiplying the measured result by a correction factor to obtaina corrected result, wherein the correction factor is the solution to anequation that specifies the correction factor as a function of themeasured result, thereby quantifying the polynucleotide analyte presentin the fluid blood sample.

Embodiment 2 is a method of quantifying a polynucleotide analyte presentin a fluid blood sample that created a dried blood spot (DBS), themethod comprising the steps of: (a) performing a nucleic acidamplification reaction using the DBS as a source of templates to produceamplification products and obtain a measured result, the measured resultindicating a concentration or an amount of the polynucleotide analyte;(b) solving an equation to determine a correction factor, wherein theequation specifies the correction factor as a function of the measuredresult; and (c) multiplying the measured result by the correction factorto obtain a corrected result, thereby quantifying the polynucleotideanalyte present in the fluid blood sample.

Embodiment 3 is the method of either embodiment 1 or 2, wherein theequation in step (b) comprises a non-linear equation.

Embodiment 4 is the method of embodiment 3, wherein the non-linearequation comprises coefficients optimized in a mathematical curvefitting procedure to define a fitted curve.

Embodiment 5 is the method of embodiment 4, wherein the non-linearequation comprises four coefficients.

Embodiment 6 is the method of any one of embodiments 1 to 5, whereinstep (a) comprises performing with an automated nucleic acid analyzerthat amplifies the polynucleotide analyte and detects amplificationproducts as the nucleic acid amplification reaction is occurring.

Embodiment 7 is the method of embodiment 6, wherein the equation in step(b) is a non-linear equation prepared using results obtained from anautomated nucleic acid analyzer different from the automated nucleicacid analyzer used for performing the nucleic acid amplificationreaction in step (a).

Embodiment 8 is the method of any one of embodiments 1 to 5, whereinstep (a) comprises performing with an automated nucleic acid analyzerthat isolates the polynucleotide analyte, and then amplifies theisolated polynucleotide analyte.

Embodiment 9 is the method of embodiment 8, wherein the automatednucleic acid analyzer further detects synthesis of amplificationproducts as the nucleic acid amplification reaction is occurring.

Embodiment 10 is the method of any one of embodiments 1 to 9, whereinthe measured result indicates a concentration of the polynucleotideanalyte in a plasma sample.

Embodiment 11 is the method of any one of embodiments 1 to 10, whereinthe nucleic acid amplification reaction is an isothermal nucleic acidamplification reaction.

Embodiment 12 is the method of embodiment 11, wherein the isothermalnucleic acid amplification reaction is a transcription-associatednucleic acid amplification reaction.

Embodiment 13 is the method of embodiment 12, wherein thetranscription-associated nucleic acid amplification reaction comprises atranscription mediated amplification (TMA) reaction.

Embodiment 14 is the method of any one of embodiments 1 to 13, whereinthe polynucleotide analyte comprises a segment of a viral genome.

Embodiment 15 is the method of embodiment 14, wherein the viral genomecomprises RNA.

Embodiment 16 is the method of any one of embodiments 1 to 15, whereinthe polynucleotide analyte comprises a segment of an HIV-1 genome.

Embodiment 17 is the method of any one of embodiments 1 to 16, whereinthe fluid blood sample comprises whole blood.

Embodiment 18 is a computer programmed with software instructions forquantifying a polynucleotide analyte present in a fluid blood samplethat dried to produce a dried blood spot (DBS), the softwareinstructions, when executed by the computer, cause the computer to: (a)receive a measured result; (b) solve an equation to determine acorrection factor, wherein the equation specifies the correction factoras a function of the measured result; (c) multiply the measured resultby the correction factor to calculate a corrected result; and (d) recordthe corrected result in a non-transient form, thereby quantifying thepolynucleotide analyte.

Embodiment 19 is the computer of embodiment 18, wherein the measuredresult is determined from results of a real-time nucleic acidamplification reaction, wherein the real-time nucleic acid amplificationreaction is carried out using the DBS as a source of templates toproduce amplification products, and wherein the measured resultindicates a concentration or an amount of the polynucleotide analyte.

Embodiment 20 is the computer of either embodiment 18 or 19, wherein themeasured result and the corrected result are both expressed inconcentration units.

Embodiment 21 is the computer of any one of embodiments 18 to 20,wherein the equation is a non-linear equation.

Embodiment 22 is the computer of embodiment 21, wherein the non-linearequation comprises coefficients optimized in a mathematical curvefitting procedure to define a fitted curve.

Embodiment 23 is the computer of embodiment 22, wherein the non-linearequation comprises four coefficients.

Embodiment 24 is the computer of any one of embodiments 18 to 23,wherein the non-transient form comprises storage on a computer-readablememory device.

Embodiment 25 is the computer of any one of embodiments 18 to 24,wherein the fluid blood sample comprises whole blood.

Embodiment 26 is a computer-readable storage medium comprisinginstructions which, when executed by a computer, cause the computer tocarry out the method of embodiment 18.

Embodiment 27 is a system for quantifying a polynucleotide analyte thatmay be present in a test sample, comprising: a nucleic acid analyzercomprising a temperature-controlled incubator; a fluorometer in opticalcommunication with the temperature-controlled incubator, wherein thefluorometer is configured to measure production of nucleic acidamplification products contained within the temperature-controlledincubator as a function of time or cycle number; and a computer incommunication with the fluorometer, wherein the computer is programmedwith software instructions causing the computer to: (a) calculate ameasured result using measurements made by the fluorometer, (b) solve anequation to determine a correction factor, wherein the equationspecifies the correction factor as a function of the measured result;(c) multiply the measured result by the correction factor to calculate acorrected result, and (d) record the corrected result in a non-transientform, thereby quantifying the target polynucleotide analyte present inthe test sample.

Embodiment 28 is the system of embodiment 27, wherein thetemperature-controlled incubator is configured to maintain a constanttemperature.

Embodiment 29 is the system of embodiment 27, wherein thetemperature-controlled incubator is configured for temperature cycling.

Embodiment 30 is the system of any one of embodiments 27 to 29, whereinthe fluorometer is configured for detecting a plurality of differentwavelengths of light.

Embodiment 31 is the system of any one of embodiments 27 to 30, whereinthe temperature-controlled incubator, the fluorometer, and the computerare all integral components of the nucleic acid analyzer.

Embodiment 32 is the system of any one of embodiments 27 to 31, whereinthe measured result comprises a concentration value for thepolynucleotide analyte.

Embodiment 33 is a method of quantifying an analyte present in a bodilyfluid sample that dried to produce a dried sample, the method comprisingthe steps of: (a) performing a reaction using the dried sample as asource of analyte to obtain a measured result, the measured resultindicating a concentration or an amount of the analyte; and (b)multiplying the measured result by a correction factor to obtain acorrected result, wherein the correction factor is the solution to anequation that specifies the correction factor as a function of themeasured result, thereby quantifying the analyte present in the bodilyfluid sample.

Embodiment 34 is the method of embodiment 33, wherein the equation instep (b) comprises a non-linear equation.

Embodiment 35 is the method of embodiment 34, wherein the non-linearequation comprises coefficients optimized in a mathematical curvefitting procedure to define a fitted curve.

Embodiment 36 is the method of embodiment 35, wherein the non-linearequation comprises four coefficients.

Embodiment 37 is the method of any one of embodiments 33 to 36, whereinthe analyte is a polynucleotide analyte, and wherein step (a) comprisesperforming with an automated nucleic acid analyzer that amplifies thepolynucleotide analyte and detects amplification products as the nucleicacid amplification reaction is occurring.

Embodiment 38 is the method of either embodiment 33 or 37, wherein theequation in step (b) comprises a non-linear equation, wherein thenon-linear equation comprises coefficients optimized in a mathematicalcurve fitting procedure to define a fitted curve, and wherein thenon-linear equation is prepared using results obtained from an automatednucleic acid analyzer different from the automated nucleic acid analyzerused for performing the nucleic acid amplification reaction in step (a).

Embodiment 39 is the method of embodiment 37, wherein step (a) comprisesperforming with an automated nucleic acid analyzer that isolates thepolynucleotide analyte, and then amplifies the isolated polynucleotideanalyte.

Embodiment 40 is the method of embodiment 39, wherein the automatednucleic acid analyzer further detects synthesis of amplificationproducts as the nucleic acid amplification reaction is occurring.

Embodiment 41 is the method of any one of embodiments 37, 39 or 40,wherein the measured result indicates a concentration of thepolynucleotide analyte in a plasma sample.

Embodiment 42 is the method of any one of embodiments 37 to 41, whereinthe nucleic acid amplification reaction is an isothermal nucleic acidamplification reaction.

Embodiment 43 is the method of embodiment 42, wherein the isothermalnucleic acid amplification reaction is a transcription-associatednucleic acid amplification reaction.

Embodiment 44 is the method of embodiment 43, wherein thetranscription-associated nucleic acid amplification reaction comprises atranscription mediated amplification (TMA) reaction.

Embodiment 45 is the method of any one of embodiments 37 to 44, whereinthe polynucleotide analyte comprises a segment of a viral genome.

Embodiment 46 is the method of embodiment 45, wherein the viral genomecomprises RNA.

Embodiment 47 is the method of any one of embodiments 37 to 46, whereinthe polynucleotide analyte comprises a segment of an HIV-1 genome.

Embodiment 48 is the method of any one of embodiments 33 to 47, whereinthe bodily fluid sample is selected from the group consisting of a wholeblood sample, a plasma sample, a urine sample, and a saliva sample.

DETAILED DESCRIPTION

Introduction and Overview

Disclosed herein is an approach for accurately converting a quantitativeresult obtained using a dried bodily fluid sample to a correspondingresult, measured in concentration units, for a liquid sample that wasused to create the dried sample. HIV nucleic acids served as the modelanalyte in the exemplary procedures. There is no need to modify thechemistries used for nucleic acid amplification and detection to achieveoutstanding results. This means that a single assay chemistry can beused to quantify a polynucleotide analyte using either liquid samples orreconstituted dry samples over a wide dynamic range. Dried blood spotsampling was used to illustrate the technique.

Rather than modifying assay chemistry, a numerical “correction factor”(hereafter CF) multiplier is used to achieve the desired results. The CFcan be multiplied by the outputted or “measured” result of aquantitative assay using a reconstituted DBS as the source of analyte.This converts the measured result to a corresponding concentration(e.g., copies/ml) of a different sample type. For example, a resultobtained using a reconstituted DBS sample can be converted or adjustedto a corresponding concentration in a whole blood sample. Thus, a singleassay chemistry (e.g., a single type of amplification and detectionreaction mixture, or a single type of assay kit) can now be used foramplifying and quantifying the polynucleotide analyte, regardless of thesample type (e.g., whole blood, plasma, reconstituted DBS, etc.).

A key feature of the present technique involves the manner in which theCF is determined. It was discovered during development of the techniquethat the required CF is not constant over the quantitative dynamic rangeof the assay. Instead, the CF varies as a function of the output of anucleic acid analyzer calibrated using a liquid sample (e.g., where theoutput can be measured in concentration units). As the amount of analytepresent in a dried sample (e.g., a DBS) undergoing reconstitution andtesting decreases, the CF required for accurate quantitation increases.

In some embodiments, the CF to be used as a numerical multiplier iscalculated using an equation fitted to a collection of data. In someembodiments, the equation is a non-linear equation. In otherembodiments, the equation can include one or more linear equations. Thedata used to obtain a fitted equation represent calculated correctionfactors as a function of the quantitative output value delivered from anucleic acid analyzer calibrated for processing liquid samples (e.g.,plasma). In some embodiments, the fitted equation used for determiningthe CF to be used on one instrument can be determined on that sameinstrument. However, it is more convenient, and so preferable, todetermine the fitted equation using one or more instruments, and then touse that fitted equation on a different instrument (i.e., an instrumentthat was not used for determining the fitted equation). For example, thefitted equation can be prepared by the manufacturer of an assay kit, andthen transferred to and used by a customer or end-user on a differentinstrument (sometimes referred to as a “local” instrument).

In some embodiments, the CF is calculated from a plurality of fittedcurves or lines, where the curve or line appropriate for CFdetermination depends on the output of the analyzer prior to applyingthe CF multiplier. Again, the CF is chosen as a function of the measuredconcentration or amount of analyte indicated to be present when testingthe dried sample (e.g., a DBS sample) after reconstitution. The chosenCF is then multiplied by that measured concentration to yield anadjusted quantitative result that quantifies the analyte.

Definitions

The following terms have the indicated meanings in the specificationunless expressly indicated to have a different meaning.

The terms “a,” “an,” and “the” include plural referents, unless thecontext clearly indicates otherwise. For example, “a polynucleotide” asused herein is understood to represent one or more polynucleotides. Assuch, the terms “a” (or “an”), “one or more,” and “at least one” can beused interchangeably herein.

As used herein, a “dried bodily fluid sample” is a sample of a bodilyfluid, such as a sample of whole blood or other blood product, where thewater component of the fluid has been substantially removed. Typically,the bodily fluid will be applied to a solid matrix (e.g., a filterpaper, a glass fiber filter, a fabric, a flocked swab, a spongematerial, etc.) prior to removal of the water component.

As used herein, a “dried blood spot” (sometimes “DBS”) refers to asample of blood or blood product that is dried prior to analysis for thepresence or amount of an analyte. Preferably, the sample of blood isapplied to a solid matrix and then permitted to dry to create or producethe DBS. In some embodiments, the solid matrix is a filter, such as apaper filter or a glass fiber filter, a fabric, a flocked swab, or asponge material. Preferably, the DBS includes a sample of dried wholeblood. Preferred analytes for testing using DBS samples includepolynucleotide analytes.

As used herein, a “reconstituted” sample is a liquid or fluid sampleresulting from combining a dried biological sample (e.g., a DBS) with aliquid (e.g., an extraction solution) that dissolves, liquifies, orresuspends the dried biological sample. In some embodiments, thereconstituted sample results from combining or contacting a dried bloodspot on a solid support matrix (e.g., a filter paper “card”) with anextraction buffer, which may include a pH buffer and a detergent. Thus,the dried blood spot can serve as a source of analyte (e.g.,polynucleotide analyte) to be detected when analyte of the reconstitutedsample is used for detection. In some embodiments, procedures fordetecting polynucleotide analytes of a reconstituted sample may involvein vitro nucleic acid amplification procedures.

As used herein, “polynucleotide” means either RNA, DNA, or a chimericmolecule containing both RNA and DNA. The term also embraces moleculescontaining nucleotide analogs of RNA or DNA.

As used herein, a “test sample” is any sample to be investigated for thepresence of a particular polynucleotide sequence. Test samples includeany polynucleotide-containing material obtained from a human, animal,environmental, or laboratory-derived or synthetic sample. Preferred testsamples include bodily fluid samples. Whole blood, plasma, and serum areparticularly preferred examples of test samples. Other test samplesinclude saliva, urine, etc.

As used herein, an “analyte” is a chemical or biochemical species thatis to be detected and/or quantified. For example, a “polynucleotideanalyte” refers to a polynucleotide (e.g., a segment of an HIV-1polynucleotide) that is to be detected or quantified in a testprocedure.

As used herein, a “nucleic acid analyzer” (or “polynucleotide analyzer”)is an apparatus that amplifies, detects, and quantifies polynucleotideanalytes. Certain preferred nucleic acid analyzers include atemperature-controlled incubator (e.g., a block, plate, or chamber), afluorometer in optical communication with contents of thetemperature-controlled incubator, and one or more computers orprocessors that process data gathered by the fluorometer to quantify apolynucleotide analyte of interest.

By “analyte polynucleotide standard” is meant a composition comprising aknown quantity of a polynucleotide analyte, or fragment thereof. Forexample, an HIV-1 analyte polynucleotide standard may contain a knownnumber of copies of an HIV-1 genome, HIV-1 transcript, or in vitrosynthesized transcript representing a portion of the viral genome. A“WHO” standard (e.g., HIV-1 WHO standard) is an analyte polynucleotidestandard of established concentration that is provided by the WorldHealth Organization.

By “calibration standard” is meant a composition that includes a knownor predetermined amount analyte polynucleotide standard in combinationwith a known constant amount of an internal calibrator polynucleotide.Two different calibration standards can contain different amounts ofpolynucleotide analyte or a fragment thereof, but will contain the sameamount of internal calibrator polynucleotide. The polynucleotide analyteof the analyte polynucleotide standard, and the internal calibratorpolynucleotide will be distinguishable from each other, for example byhaving nucleotide base sequences that are different. A test instrument(e.g., a nucleic acid analyzer) is said to be “calibrated” when acalibration standard has been used to ensure the instrument deliversaccurate results. For example, an instrument may be calibrated todeliver accurate results when processing plasma samples.

An “amplicon” (sometimes “amplification product”) is a polynucleotideproduct of an amplification reaction, wherein a target polynucleotidesequence of a polynucleotide analyte served as the template forsynthesis of polynucleotide copies or amplification products.

By “amplification” or “nucleic acid amplification” or “polynucleotideamplification” and the like is meant any known procedure for obtainingmultiple copies, allowing for RNA and DNA equivalents, of a targetpolynucleotide sequence or its complement or fragments thereof.Amplification of “fragments thereof” refers to production of anamplified nucleic acid (i.e., polynucleotide) containing less than thecomplete target region nucleic acid sequence or its complement. Suchfragments may be produced by amplifying a portion of the target nucleicacid, for example, by using an amplification oligonucleotide thathybridizes to, and initiates polymerization from, an internal positionof the target polynucleotide.

As used herein, the terms “coamplify” and “coamplifying” and variantsthereof refer to a process wherein different target polynucleotidesequences are amplified in a single (i.e., the same) amplificationreaction. For example, a polynucleotide analyte and an unrelatedinternal calibrator polynucleotide are “coamplified” when bothpolynucleotides are amplified in reactions taking place in a singletube, and when both amplification reactions share at least one reagent(e.g., deoxyribonucleotide triphosphates, enzyme, primer(s), etc.) incommon.

As used herein, “thermal cycling” refers to repeated changes oftemperature, (i.e., increases or decreases of temperature) in a reactionmixture. Samples undergoing thermal cycling may shift from onetemperature to another, stabilize at that temperature, transition to asecond temperature or return to the starting temperature. Thetemperature cycle may be repeated as many times as required to study orcomplete the particular chemical reaction of interest.

By “target” or “target nucleic acid” or “target polynucleotide” is meanta polynucleotide containing a sequence that is to be amplified, detectedand quantified. A target polynucleotide sequence that is to be amplifiedpreferably will be positioned between two oppositely disposedoligonucleotides, and will include the portion of the targetpolynucleotide that is complementary to each of the oligonucleotides.

By “target polynucleotide sequence” or “target sequence” or “targetregion” is meant a specific deoxyribonucleotide or ribonucleotidesequence comprising all or part of the nucleotide sequence of asingle-stranded polynucleotide molecule, and the deoxyribonucleotide orribonucleotide sequence complementary thereto.

By “transcription-associated amplification” is meant any type ofpolynucleotide amplification that uses an RNA polymerase to producemultiple RNA transcripts from a polynucleotide template. Conventionally,these amplification reactions employ at least one primer having a 3-endthat can be extended by the activity of a DNA polymerase. One example ofa transcription-associated amplification method, called “TranscriptionMediated Amplification” (TMA), generally employs an RNA polymerase, aDNA polymerase, deoxyribonucleoside triphosphates, ribonucleosidetriphosphates, and a promoter-containing oligonucleotide complementaryto the target polynucleotide. Variations of TMA are well known in theart as disclosed in detail in Burg et al., U.S. Pat. No. 5,437,990;Kacian et al., U.S. Pat. Nos. 5,399,491 and 5,554,516; Kacian et al.,PCT No. WO 93/22461; Gingeras et al., PCT No. WO 88/01302; Gingeras etal., PCT No. WO 88/10315; Malek et al., U.S. Pat. No. 5,130,238; Urdeaet al., U.S. Pat. Nos. 4,868,105 and 5,124,246; McDonough et al., PCTNo. WO 94/03472; and Ryder et al., PCT No. WO 95/03430. Othertranscription-associated amplification methods employing only a singleprimer that can be extended by a DNA polymerase, as disclosed in theU.S. Pat. No. 7,374,885 are particularly embraced by the definition andare highly preferred for use in connection with the method disclosedherein.

As used herein, an “oligonucleotide” or “oligomer” is a polymeric chainof at least two, generally between about five and about 100, chemicalsubunits, each subunit comprising a nucleotide base moiety, a sugarmoiety, and a linking moiety that joins the subunits in a linear spatialconfiguration. Common nucleotide base moieties are guanine (G), adenine(A), cytosine (C), thymine (T) and uracil (U), although other rare ormodified nucleotide bases able to hydrogen bond are well known to thoseskilled in the art. Oligonucleotides may optionally include analogs ofany of the sugar moieties, the base moieties, and the backboneconstituents. Preferred oligonucleotides of the present invention fallin a size range of about 10 to about 100 residues. Oligonucleotides maybe purified from naturally occurring sources, but preferably aresynthesized using any of a variety of well-known enzymatic or chemicalmethods.

By “amplification oligonucleotide” or “amplification oligomer” is meantan oligomer that hybridizes to a target polynucleotide, or itscomplement, and participates in a polynucleotide amplification reaction.Examples of amplification oligomers include primers that contain a 3-endthat is extended as part of the amplification process, but also includeoligomers that are not extended by a polymerase (e.g., a 3-blockedoligomer) but may participate in, or facilitate efficient amplificationfrom a primer. Preferred size ranges for amplification oligomers includethose that are about 10 to about 80 nucleotides long, or 10 to about 60nucleotides long and contain at least about 10 contiguous bases, andmore preferably at least 12 contiguous bases that are complementary to aregion of the target polynucleotide sequence (or a complementary strandthereof). The contiguous bases are preferably at least about 80%, morepreferably at least about 90%, and most preferably about 100%complementary to the target sequence to which amplification oligomerbinds. An amplification oligomer may optionally include modifiednucleotides or analogs, or additional nucleotides that participate in anamplification reaction but are not complementary to or contained in thetarget polynucleotide. An amplification oligomer that is 3-blocked butcapable of hybridizing to a target polynucleotide and providing anupstream promoter sequence that serves to initiate transcription isreferred to as a “promoter provider” oligomer.

A “primer” is an amplification oligomer that hybridizes to a templatepolynucleotide and has a 3-OH end that can be extended by a DNApolymerase. The 5′ region of the primer may be non-complementary to thetarget polynucleotide (e.g., a promoter sequence), resulting in anoligomer referred to as a “promoter-primer.” Those skilled in the artwill appreciate that any oligomer that can function as a primer can bemodified to include a 5′ promoter sequence, and thus could function as apromoter-primer. Similarly, any promoter-primer can be modified byremoval of, or synthesis without, a promoter sequence and still functionas a primer.

As used herein, a “probe” is an oligonucleotide that hybridizesspecifically to a target sequence in a polynucleotide, preferably in anamplified polynucleotide, under conditions that promote hybridization,to form a detectable hybrid. Certain preferred probes include adetectable label (e.g., a fluorescent label or chemiluminescent label).

As used herein, “time-dependent” monitoring of polynucleotideamplification, or monitoring of polynucleotide amplification in“real-time” refers to a process wherein the amount of amplicon presentin a polynucleotide amplification reaction is measured as a function ofreaction time or cycle number, and then used to determine a startingamount of template that was present in the reaction mixture at the timethe amplification reaction was initiated. For example, the amount ofamplicon can be measured prior to commencing each complete cycle of anamplification reaction that comprises thermal cycling, such as PCR.Alternatively, isothermal amplification reactions that do not requirephysical intervention to initiate the transitions between amplificationcycles can be monitored continuously, or at regular time intervals toobtain information regarding the amount of amplicon present as afunction of time.

As used herein, a “growth curve” refers to the characteristic pattern ofappearance of a synthetic product, such as an amplicon, in a reaction asa function of time or cycle number. A growth curve is convenientlyrepresented as a two-dimensional plot of time or cycle number (x-axis)against some indicator of product amount, such as a fluorescencemeasurement (y-axis). Some, but not all, growth curves have asigmoid-shape.

As used herein, the “baseline phase” of a growth curve refers to theinitial phase of the curve wherein the amount of product (such as anamplicon) increases at a substantially constant rate, this rate beingless than the rate of increase characteristic of the growth phase (whichmay have a log-linear profile) of the growth curve. The baseline phaseof a growth curve typically has a very shallow slope, frequentlyapproximating zero.

As used herein, the “growth phase” of a growth curve refers to theportion of the curve wherein the measurable product substantiallyincreases with time. Transition from the baseline phase into the growthphase in a typical polynucleotide amplification reaction ischaracterized by the appearance of amplicon at a rate that increaseswith time. Transition from the growth phase to the plateau phase of thegrowth curve begins at an inflection point where the rate of ampliconappearance begins to decrease.

As used herein, the “plateau phase” of a triphasic growth curve refersto the final phase of the curve. In the plateau phase, the rate ofmeasurable product formation generally is substantially lower than therate of amplicon production in the log-linear phase, and may evenapproach zero.

As used herein, the phrase “indicia of amplification” refers to featuresof real-time run curves which indicate a predetermined level of progressin polynucleotide amplification reactions. Such indicia are commonlydetermined by mathematical analysis of run curves, sometimes referred toas “growth curves,” which display a measurable signal (such as afluorescence reading) whose intensity is related to the quantity of anamplicon present in a reaction mixture as a function of time, cyclenumber, etc.

As used herein, the phrase “threshold-based indicia of amplification”refers to indicia of amplification that measure the time or cycle numberwhen a growth curve signal crosses an arbitrary value or threshold.TTime determinations are examples of threshold-based indicia ofamplification, while TArc and OTArc determinations are examples ofnon-threshold-based indicia of amplification.

As used herein, the phrase “time-dependent” indicia of amplificationrefers generally to indicia of amplification (e.g., a reaction progressparameter) that are measured in time units (e.g., minutes).Time-dependent indicia of amplification are commonly used for monitoringprogress in isothermal polynucleotide amplification reactions that arenot characterized by distinct “cycles.” All of TTime, TArc and OTArc areexamples of time-dependent indicia of amplification.

As used herein, an “internal calibrator” (sometimes “IC” herein) is apolynucleotide that can be amplified in an in vitro polynucleotideamplification reaction, and that is distinguishable from apolynucleotide analyte that coamplified in the same reaction. “Internal”means that the calibrator polynucleotide is amplified, detected andquantified within the same reaction mixture as the polynucleotideanalyte, or fragment thereof. Generally speaking, the amount orconcentration of the internal calibrator will be constant in differentreactions used for preparing calibration curves, and for quantifying thepolynucleotide analyte. Preferably, the constant amount or concentrationof internal calibrator will be a known amount of internal calibrator, ora known concentration of internal calibrator. In certain preferredembodiments, the internal calibrator and the polynucleotide analyte arecoamplified in an in vitro polynucleotide amplification reaction usingone or more different amplification oligomers or primers. For example,the analyte and internal calibrator polynucleotides employed in theworking Examples detailed below were amplified using amplificationoligonucleotides that were not shared. In other preferred embodiments,the internal calibrator and the polynucleotide analyte are coamplifiedin an in vitro polynucleotide amplification reaction using one or moreidentical amplification oligomers or primers.

As used herein, the phrase “as a function of” describes the relationshipbetween a dependent variable (i.e., a variable that depends on one ormore other variables) and an independent variable (i.e., a variable thatmay have its value freely chosen without considering the values of anyother variables), wherein each input value for the independent variablerelates to exactly one output value for the dependent variable.Conventional notation for an equation that relates a y-value (i.e., thedependent variable) “as a function of” an x-value (i.e., the independentvariable) is y=f(x).

As used herein, a “computer” is an electronic device capable ofreceiving and processing input information to generate an output. Thecomputer may be a standalone device (e.g., a personal computer), or maybe an integrated component of an instrument (e.g., a nucleic acidanalyzer that amplifies a polynucleotide target and monitors synthesisof amplification products as a function of reaction cycle number ortime). Particularly embraced by the term is an embedded processorresident within an analyzer instrument, and harboring embedded softwareinstructions (sometimes referred to a “firmware”).

As used herein, “optimizing” or “fitting” an equation refers to aprocess, as commonly practiced in mathematical modeling or curve fittingprocedures, for obtaining numerical values for coefficients in anequation to yield an expression that “fits” or approximates experimentalmeasurements. Typically, an optimized equation will define a best-fitcurve.

As used herein, the terms “optimized equation,” and “fitted equation”are alternative references to an equation containing fixed numericalvalues for coefficients as the result of an optimizing procedure.“Fitted” curves result from optimizing an equation.

By “local” is meant relating to an end-user. For example, a localinstrument refers to an end-user's instrument. A local calibration plotrefers to a calibration plot using results obtained by an end-user, forexample by conducting an amplification reaction on the local instrument.

By “kit” is meant a packaged combination of materials, typicallyintended for use in conjunction with each other. Kits in accordance withthe invention may include instructions or other information in a“tangible” form (e.g., printed information, electronically recorded on acomputer-readable medium, or otherwise recorded on a machine-readablemedium such as a bar code for storing numerical values).

By “consisting essentially of” is meant that additional component(s),composition(s) or method step(s) that do not materially change the basicand novel characteristics of the present invention may be included inthe present invention. Any component(s), composition(s), or methodstep(s) that have a material effect on the basic and novelcharacteristics of the present invention would fall outside of thisterm.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a plot of calculated correction factor (CF) values (verticalaxis) as a function of the “observed” or “measured” concentration(measured in copies/ml) of an HIV-1 polynucleotide analyte (horizontalaxis). Open circular data points represent calculated CF values atdifferent measured target concentrations in a procedure that amplifiedpolynucleotide analyte from reconstituted DBS samples. A solid curve hasbeen fitted to the collected data points by mathematically optimizing a4-PL equation.

DESCRIPTIONS OF CERTAIN EMBODIMENTS

The presently disclosed technique was demonstrated using the Aptima™HIV-1 Quant Dx assay from Hologic, Inc., (Marlborough, Mass.) as a modelsystem. This viral load monitoring assay is both highly sensitive andspecific, and can be used to assess responses to antiretroviraltreatment by monitoring changes in the concentration of HIV-1 RNA. Theassay is an in vitro polynucleotide amplification test for the detectionand quantification of human immunodeficiency virus type 1 (HIV-1) RNAgroups M, N, and O that can be performed on the fully automated Panther™system (Hologic, Inc.). The system running the viral load assay iscalibrated to output a concentration of virus, measured in copies/mlusing a 500 μl test sample. For example, the model assay can be used formonitoring the effect of antiviral treatment by measuring changes in theconcentration of HIV-1 RNA in plasma. There would be a benefit foraccurately correlating quantitative results obtained using DBS samplesand plasma samples using the same calibration as well as reagents, andprotocol for target capture, amplification and detection.

The model assay involves three main steps, which all take place in asingle tube on the automated Panther system for polynucleotide analysis:target capture, target amplification by Transcription MediatedAmplification, and detection of the amplification products (amplicon) bythe fluorescently labeled hybridization probes (torches). During targetcapture, the specimen is treated with a detergent to solubilize theviral envelope, denature proteins, and release viral genomic RNA.Capture oligonucleotides hybridize to highly conserved regions of theHIV-1 genome, if present, in the test sample. The hybridized target isthen captured onto magnetic microparticles that are separated from thespecimen in a magnetic field. Wash steps remove extraneous componentsfrom the reaction tube. Target amplification then occurs via TMA, whichis a transcription-mediated polynucleotide amplification method thatutilizes two enzymes, MMLV (Moloney murine leukemia virus) reversetranscriptase and T7 RNA polymerase. The reverse transcriptase is usedto generate a DNA copy (containing a promoter sequence for T7 RNApolymerase) of the target sequence. T7 RNA polymerase produces multiplecopies of RNA amplicon from the DNA copy template. The model assayutilizes the TMA method to amplify two regions of HIV-1 RNA (pol andLTR). Amplification of these specific regions is achieved using specificprimers which are designed to amplify HIV-1 groups M, N, and O. Theprimer design and dual target approach ensure accurate detection andquantitation of HIV-1. Detection is achieved using single-strandedpolynucleotide torches that are present during the amplification of thetarget and that hybridize specifically to the amplicon in real-time.Each torch has a fluorophore and a quencher. When the torch is nothybridized to the amplicon, the quencher is in close proximity to thefluorophore, and so suppresses fluorescence. When the torch binds to theamplicon, the quencher is moved farther away from the fluorophore andemits a signal at a specific wavelength when excited by a light source.A higher fluorescent signal is generated as more torches hybridize toamplicon. The time taken for the fluorescent signal to reach a specifiedthreshold is proportional to the starting HIV-1 concentration. Eachreaction has an internal calibrator/internal control (IC) thatcoamplifies with the HIV-1 analyte and controls for variations inspecimen processing, amplification, and detection. The concentration ofa sample is determined by the Panther system software using the HIV-1and IC signals for each reaction and comparing them to calibrationinformation. Determined concentrations are calibrated for HIV-1 inplasma samples, and not for reconstituted DBS samples. The determinedconcentration here can alternatively be referred to as an “observed”result or a “measured” result.

There are different types of DBS, and each can be used for performingthe quantitative technique described herein. Blood samples can beobtained from infants using standard heal stick or finger sticktechniques. Here the skin surface of the infant is disinfected and thenpricked with a sterile needle or lancet. Next, 3-5 drops of blood can beadded to each of a plurality (e.g., 5) of spots on a DBS “card,”ensuring that the entire surface of the circle is completely filled. Thefinger stick technique also can be used with adults to obtain DBSsamples. Whole blood conveniently may be stored for up to 24 hours at 2°C. to 30° C. prior to application to the DBS cards. In this instance, 70μl of stored whole blood can be applied to the center of a filter circleon a DBS card, for example using a calibrated 200 μl pipette. Spottedblood samples, however obtained, can be dried at ambient temperature for4-24 hours. Individual cards harboring the dried samples can be placedinto an envelope (e.g., a glassine envelope) for storage or transport.Multiple glassine envelopes can be packaged into a resealable plasticbag with one or more desiccant packs. However they are packaged, DBSsamples can be held or shipped at ambient temperatures for subsequentprocessing.

Preferred Polynucleotide Amplification Methods

Examples of in vitro polynucleotide amplification methods useful inconnection with the present technique include, but are not limited to:Transcription Mediated Amplification (TMA), Single-Primer Nucleic AcidAmplification, Nucleic Acid Sequence-Based Amplification (NASBA), thePolymerase Chain Reaction (PCR), Strand Displacement Amplification(SDA), Self-Sustained Sequence Replication (3SR), DNA Ligase ChainReaction (LCR) and amplification methods using self-replicatingpolynucleotide molecules and replication enzymes such as MDV-1 RNA andQ-beta enzyme. Methods for carrying out these various amplificationtechniques respectively can be found in U.S. Pat. No. 5,399,491, U.S.patent application Ser. No. 11/213,519, published European patentapplication EP 0 525 882, U.S. Pat. Nos. 4,965,188, 5,455,166, Guatelliet al., Proc. Natl. Acad. Sci. USA 87:1874-1878 (1990), InternationalPublication No. WO 89/09835, U.S. Pat. No. 5,472,840 and Lizardi et al.,Trends Biotechnol. 9:53-58 (1991). The disclosures of these documentswhich describe how to perform polynucleotide amplification reactions arehereby incorporated by reference. Thus, although the model system usedfor demonstrating the correction factor adjustment technique employedTMA as the amplification reaction mechanism, alternative amplificationreaction mechanisms also can be used with equally good results.

Examples of Preferred Real-Time Quantitative Techniques

Generally speaking, real-time polynucleotide amplification and detectionprocedures involve monitoring production of amplification reactionproducts as the amplification reaction is occurring. As indicated above,any number of different amplification methods can be used to createamplification products. In some embodiments, synthesis of amplificationproducts as a function of time or cycle number is indicated by detectionof a fluorescent signal generated in the amplification reaction mixture.Examples of methods useful for calibrating instruments carrying outreal-time amplification reactions are given in U.S. Pat. Nos. 9,932,628and 9,976,175, the disclosures of these patents being incorporated byreference herein for all purposes. Success of these methods isindependent of the manner in which run curves in the real-timeprocedures are obtained. Stated differently, different indicia ofamplification can be used to establish when an amplification reactionhas achieved a desired threshold level of amplification progress.

A variety of indicia of amplification can be used for quantifyinganalytes before the CF adjustment is applied to the data. Real-timeamplification and detection for quantifying polynucleotide analytes ishighly preferred for use in connection with the disclosed CF adjustmenttechnique, and is subject to alternative data processing procedures withgood results in each case. For example, mathematical and computingtechniques that will be familiar to those having an ordinary level ofskill in the art can be used to identify the time of occurrence of themaximum of the first derivative, or the time of occurrence of themaximum of the second derivative of a real-time run curve. Approachesfor determining these features of a growth curve have been detailed byWittwer et al., in U.S. Pat. No. 6,503,720, the disclosure of which isincorporated by reference herein. Other useful approaches involvecalculating a derivative of a growth curve, identifying a characteristicof the growth curve, and then determining the threshold time or cyclenumber corresponding to the characteristic of the derivative. Suchtechniques have been disclosed in U.S. Pat. No. 6,783,934, thedisclosure of which is incorporated by reference. Still other usefulindicia of amplification include “TTime” and “TArc.” Differentapproaches for determining TArc values employ directionally similarvectors (i.e., resulting in a value identified simply by “TArc”), anddirectionally opposed vectors (i.e., resulting in a value identified as“OTArc”). Still other techniques involve identifying cycle threshold(e.g., “Ct”) values as the time or cycle number during a reaction atwhich a signal, preferably a fluorescent signal, equals a staticthreshold (e.g., a predetermined static threshold value).

Preferred Systems and Apparatus

The methods disclosed herein are conveniently implemented using acomputer or similar processing device (“computer” hereafter). Indifferent preferred embodiments, software or machine-executableinstructions for performing an algorithm can be loaded or otherwise heldin a memory component of a freestanding computer, or in a memorycomponent of a computer linked to a device used for monitoring,preferably as a function of time, the amount of a product undergoinganalysis. In a highly preferred embodiment, software for executing thecorrection factor adjustment procedure is held in a memory component ofa computer that is linked to, or that is an integral part of a devicecapable of monitoring the amount of an amplicon present in a reactionmixture as a function of time. This includes a processing devicecomponent on an electronic circuit board (e.g., embedded software) of anautomated nucleic acid analyzer.

In some embodiments, the computer can be in communication with, eitherby wired or wireless means, a fluorometer that detects fluorescentsignals, where the fluorometer is arranged or configured to monitorfluorescent signals generated in one or more reaction vessels containedwithin a temperature-controlled incubator. The incubator can be atemperature-controlled block (e.g., a metal block configured forreceiving and containing one or more tubes, or even a multi-well plate),or a chamber that exposes one or more reaction vessels to controlledtemperature conditions.

In some embodiments, either or both of a controller system forcontrolling a real-time amplification device and/or the detection systemof the real-time amplification device can be coupled to an appropriatelyprogrammed computer which functions to instruct the operation of theseinstruments in accordance with preprogrammed or user input instructions.The computer preferably also can receive data and information from theseinstruments, and interpret, manipulate and report this information tothe user.

In some embodiments, the computer also can include appropriate softwarefor receiving user instructions, either in the form of user input into aset of parameter fields, or in the form of preprogrammed instructions(e.g., preprogrammed for a variety of different specific operations).The software then converts these instructions to appropriate languagefor instructing the operation of the real-time amplification controllerto carry out the desired operation. Preferably, the computer also iscapable of receiving data from one or more sensors/detectors includedwithin the system, and interprets the data in accordance with theprogramming. The system preferably includes software that correlates afeature of a growth curve representing the quantity of amplified copiesof the polynucleotide of interest as a function of time, as detected bythe detector, to the number of copies of the polynucleotide of interestpresent in a test sample.

Preferably, when the computer used for executing the disclosed CFdetermination and adjustment procedure is an integral component of anapparatus for performing and analyzing real-time polynucleotideamplification reactions, the apparatus preferably comprises atemperature-controlled incubator, a detection device for collectingsignals (e.g., a fluorometer), and an analyzing device (e.g., a computeror processor) for analyzing signals. The apparatus optionally canfurther include an output device for displaying data obtained orgenerated. The analyzing device may be connected to thetemperature-controlled incubator through an input device known in theart, and/or connected to an output device known in the art for datadisplay. In one embodiment, the temperature-controlled incubator iscapable of temperature cycling.

Generally speaking, the various components of an apparatus forperforming the real-time polynucleotide amplification useful inconnection with the disclosed methods will be conventional componentsthat will be familiar to those having an ordinary level of skill in theart. The temperature-controlled incubator used to perform and analyzereal-time polynucleotide amplification may be of a conventional designwhich can hold a plurality of reaction tubes, or reaction samples in atemperature-controlled block in standard amplification reaction tubes orin wells of a multiwell plate. In one aspect, the detection system issuitable for detecting optical signals from one or more fluorescentlabels. The output of the detection system (e.g., signals correspondingto those generated during the amplification reaction) can be fed to thecomputer for data storage and manipulation. In one embodiment, thesystem detects multiple different types of optical signals, such asmultiple different types of fluorescent labels and has the capabilitiesof a microplate fluorescence reader. The detection system is preferablya multiplexed fluorimeter containing an excitation light source, whichmay be a visible light laser or an ultraviolet lamp or a halogen lamp, amultiplexer device for distributing the excitation light to theindividual reaction tubes and for receiving fluorescent light from thereaction tubes, a filtering means for separating the fluorescence lightfrom the excitation light by their wavelengths, and a detection meansfor measuring the fluorescence light intensity. Preferably, thedetection system of the temperature-controlled incubator provides abroad detection range that allows flexibility of fluorophore choice,high sensitivity and excellent signal-to-noise ratio. Optical signalsreceived by the detection system are generally converted into signalswhich can be operated on by the processor to provide data which can beviewed by a user on a display of a user device in communication with theprocessor. The user device may comprise a user interface or may be aconventional commercially available computer system with a keyboard andvideo monitor. Examples of data which can be displayed by the userdevice include amplification plots, scatter plots, sample value screensfor all the tubes or reaction vessels in the assembly and for all labelsused, an optical signal intensity screen (e.g., fluorescent signalintensity screen), final call results, text reports, and the like.

Computer Program Products

Included within the scope of the invention are software-based products(e.g., tangible embodiments of software for instructing a computer toexecute various procedural steps) that can be used for performing thedata processing method. These include software instructions stored oncomputer-readable media, such as magnetic media, optical media, “flash”memory devices, and computer networks or cloud storage. As well, theinvention embraces a system or an apparatus that amplifiespolynucleotides, detects polynucleotide amplification products, andprocesses results to indicate a quantitative result for target in a testsample. Although the various components of the apparatus preferablyfunction in a cooperative fashion, there is no requirement for thecomponents to be part of an integrated assembly (e.g., on a singlechassis). However, in a preferred embodiment, components of theapparatus are connected together. Included within the meaning of“connected” are connections via wired and wireless connections.

Particularly falling within the scope of the invention is an apparatusor system that includes a computer linked to a device that amplifiespolynucleotides and monitors amplicon synthesis as a function of cyclenumber or time, where the computer is programmed to execute thequantitative algorithm disclosed herein. An exemplary system inaccordance with the invention will include a temperature-controlledincubator, and a fluorometer capable of monitoring and distinguishing atleast two wavelengths of fluorescent emissions. These emissions may beused to indicate target amplicon synthesis, and IC amplicon synthesis.

In connection with computer-implemented or software-implementedembodiments of the disclosure, a result can be recorded or stored in a“non-transient” format where it can be accessed for reference at a latertime than when the data analysis to be recorded was carried out orperformed. For example, a computed result can be recorded in anon-transient format by printing on paper, or by storing on acomputer-readable memory device (e.g., a hard drive, flash memorydevice, file in cloud storage, etc.).

Curve Fitting Procedures

In accordance with the disclosed method of creating a curve, plot, orfitted equation for determining correction factors, the relatingprocedure or step preferably involves obtaining one or more equationsoptimized to fit a data set. The data set comprises calculated CF valuesas a function of a result produced by a nucleic acid analyzer calibratedfor determining the amount of analyte in a known volume of liquidsample. This can be accomplished by applying standard mathematical curvefitting techniques to each of the data sets to result in a fittedequation that defines a curve associated therewith. In some embodiments,one or more linear equations can be used for determining an appropriateCF from the output of a nucleic acid analyzer calibrated to deliverquantitative results for samples of a type (e.g., plasma samples) otherthan a reconstituted DBS sample. In other embodiments, the equation usedin the curve fitting procedure preferably is a non-linear equation thatcontains no less than two, more preferably no less than three, and morepreferably no less than four coefficients that can be optimized ordetermined during the curve fitting procedure. Some highly preferredequations have exactly four coefficients, while other highly preferredequations have exactly five coefficients. Optimizing an equation to fitthe measured indicia of amplification can easily be accomplished using acommercially available software package, such as the SOLVER programwhich is available as an EXCEL add-in tool for finding an optimal valuefor a formula, and equation solving from Microsoft Corporation (Redmond,Wash.). Certain curves generated by this procedure can be shaped suchthat increasing levels of the polynucleotide analyte input into areaction correlate with reduced CF values.

Although other equations can be used in the curve fitting procedure, themethods described below employed a four-parameter logistic (4-PL)equation having the following form:

$\begin{matrix}{{CF} = {c + \frac{d - c}{\left( {1 + {\exp\hat{}\left( {b*\left( {x - e} \right)} \right)}} \right)}}} & \left( {{Eq}1} \right)\end{matrix}$

In this equation, the CF dependent variable represents the correctionfactor as a function of the observed or measured concentration (x) inlogarithmic scale of the polynucleotide analyte. Again, the “observed”or “measured” concentration is the quantitative output of an assaycalibrated for detecting the HIV-1 polynucleotide analyte in a testsample, but need not be calibrated for quantifying the analyte in areconstituted DBS sample. The four coefficients in the equation that canbe optimized by standard procedures are identified as b to e. The “exp”constant is the base of the natural logarithm (i.e., about 2.7183). Ofcourse, it is to be understood that success in using the presentinvention does not require the use of any particular equation.

Alternative Equations for Performing Curve Fitting

Notably, although a 4-PL equation was used for illustrating thedisclosed technique, other mathematical functions can also be used inthe procedure to simulate the trend of CF values versus measuredoutputs.

Those having an ordinary level of skill in the art will appreciate thatnumerous types of equations may be used in the procedures disclosedherein. Examples of symmetric transition functions include, but are notlimited to: Sigmoid, Gaussian Cumulative, Lorentzian Cumulative andCumulative Symmetric Double Sigmoidal. Examples of asymmetric transitionfunctions include, but are not limited to: Logistic Dose Response (LDR),Log Normal Cumulative, Extreme Value Cumulative, Pulse Cumulative, PulseCumulative with Power Term, Weibull Cumulative, Asymmetric Sigmoid,Asymmetric Sigmoid Reverse Asymmetry, Cascade Formation, and CumulativeExponentially Modified Gaussian. Additionally, simple linear andnon-linear equations, such as multiple order polynomials, power,exponential and logarithmic functions can be used to model real-timedata with subsequent adjustment of the baseline coefficient, as detailedherein. Kinetic functions with baseline coefficients can also be used inthe same manner. Exemplary basic kinetic equations containing baselinecoefficients include but are not limited to: Half Order Decay andFormation, First Order Decay and Formation, Second Order Decay andFormation, Second Order Decay and Formation (Hyperbolic Forms), andThird Order Decay and Formation, Variable Order Decay and Formation.Exemplary complex kinetic equations containing baseline coefficientsinclude but are not limited to: Simultaneous First and Second OrderDecay and Formation, First Order Sequential Formation, Two ComponentFirst Order Decay, Two First Order Independent Decay and Formation, TwoSecond Order Independent Decay and Formation, and First and Second OrderIndependent Decay and Formation. Exemplary kinetic equilibrium equationscontaining baseline coefficients include but are not limited to: SimpleEquilibrium (Forward and Reverse Rate), Simple Equilibrium (Net Rate andEquilibrium Concentration), Complex Equilibrium A=B+C, and ComplexEquilibrium A+B=C+D. Exemplary intermediate kinetic equations containingbaseline coefficients include but are not limited to: First OrderIntermediate and First Order Intermediate with Equilibrium. One ofordinary skill in the art will readily understand that success of thedisclosed CF adjustment method does not depend on the use of anyparticular equation for performing the curve fitting step. Indeed, it isbelieved that any equation having coefficients that can be optimized ina curve fitting procedure for the disclosed CF adjustment procedures.

All of the above-listed equation types can be used to carry out thedisclosed methods. This is because success of the procedure depends noton the particular equation used, but on its ability to fit the dataoptimally.

WORKING EXAMPLES

As stated above, the disclosed technique improved the quantitativecapacity of assays carried out using dried bodily fluid samples bydelivering reliable results that correlated with concentrations ofpolynucleotide analyte in the starting sample that was used to createthe dry sample. The Examples presented below are intended to beillustrative, and are not intended to limit the disclosure in any way.

Those having an ordinary level of skill in the art will appreciate thatthe lower limit of quantification (“LLOQ”) in an assay is the lowestconcentration of an analyte that can be quantified with a certain levelof accuracy and precision, and have at least 95% reactivity. Likewise,those having an ordinary level of skill in the art will appreciate thatthe limit of detection (“LOD”) in an assay is the lowest concentrationof analyte that can be consistently detected in at least 95% of testedsamples.

The LLOQ of an assay is the minimum concentration at which the followingtwo requirements are met: (1) reactivity should be at least 95%; and (2)total error (TE) should meet specifications for assay accuracy. In thecase of the model viral load assay used for illustrating the present CFadjustment technique, the TE specification is ≤1 log accuracy at theLLOQ. Two different “total error” assessment approaches were used togauge the impacts of different correction factor approaches at the lowerlimit of quantification (LLOQ). These approaches were the CLSI EP-17-A2guideline recommended Westgard, and the root mean square (RMS) modelsfor calculation of LLOQ. The procedure involved determining accuracy andprecision of quantification at low HIV concentrations usingreconstituted DBS samples as the source of analyte. Stocks of a dilutedWHO HIV standard having an assigned concentration value, which served asthe “gold standard” for quantification, were used to create DBS samples.More particularly, various amounts of HIV WHO standard stock were spikedinto different aliquots of whole blood, and the resulting dilutions usedto prepare DBS samples.

In accordance with the above-cited Westgard model, the TE can becalculated using the following equation.

Bias+(2×Std Dev)≤1 log  (Eq 2)

In accordance with the above-cited RMS model, the TE can be calculatedusing the following equation.

√{square root over ((Bias)²+(Std Dev)²)}≤1 log  (Eq 3)

In the context of these equations, “bias” is the difference between theexpected (i.e., actual) and the “recovered” assay result. As usedherein, a “recovered” result has been adjusted using a CF multiplier,and so differs from a measured result, which has not been adjusted usinga CF multiplier. Simply stated, a recovered result can be calculated bymultiplying a measured result by a CF. The CF adjustment is able toimprove assay quantification at low analyte concentrations by reducingbias (improving accuracy) and improving precision (by reducing Std.Dev.).

An initial approach to improve DBS quantification involved the use ofstatic (i.e., constant) CF value multipliers. More specifically,pre-selected constants in the range of from 15 to 33 were multiplied bythe measured value of a real-time polynucleotide amplification assaythat was calibrated to deliver quantitative results for a 500 μl liquidsample (e.g., plasma). It is important for assays that measure HIV viralload to meet accuracy goals at concentrations≤1,000 copies/ml. This isbecause the WHO recommended medical decision point for monitoringeffectiveness of antiretroviral treatment is 1,000 copies/ml. Therefore,clinical sensitivity and specificity of the assay was calculated at themedical decision point of 1,000 copies/ml using recovered assay resultsfor DBS calculated using different static CFs. No significant differencein assay sensitivity or specificity was seen when CFs ranging from 25 to33 were used. According to one approach, the LOD determined forreconstituted DBS samples (i.e., 873 copies/ml) was divided by the LLOQfor plasma samples (i.e., 30 copies/ml) for the same assay chemistry toestablish a constant CF value of 29.1 for use as a multiplier. Thus, anassay conducted using a 500 μl aliquot of a reconstituted DBS sample(e.g., a filter having been spotted with 70 μl of whole blood and thendried, and subsequently reconstituted with 1 ml of buffer) that yieldeda “measured” or observed output of 35 copies/ml would be multiplied by29.1 to give a corrected (i.e., “recovered”) result of 1,019 copies/ml.

Example 1 describes a real-time polynucleotide amplification assay thatquantified HIV-1 polynucleotides using reconstituted DBS samples. Theautomated nucleic acid analyzer used in the procedure was calibrated todeliver results measured in copies/ml for plasma samples.

Example 1 Static Correction Factor Quantifies Polynucleotide Analytewith Excessive Error

DBS samples harboring known quantities of HIV-1 polynucleotides wereprepared using laboratory procedures that will be familiar to thosehaving an ordinary level of skill in the art. Whole blood was spikedwith HIV-1 from the value assigned WHO standard virus stock to producesamples having concentrations in the range of from 50 copies/ml to 1,200copies/ml. Whole blood samples (70 μl each) of the different HIVconcentrations were separately applied to standard filter paper cards,and then allowed to dry. Dried blood spots were punched from the cardsand each DBS was combined with 1 ml of a buffered detergent solution(i.e., DBS extraction buffer). One-half of each sample (500 μl) was thenused for testing in the Aptima HIV-1 Quant Dx real-time viral load assayon the Panther automated nucleic acid analyzer (Hologic, Inc.;Marlborough, Mass.). At least 90 replicates of DBS samples tested usingdifferent HIV-1 reagent lots on the platform yielded essentiallyequivalent outcomes. Table 1 presents illustrative results obtainedusing one of the reagent lots. Columns 1 and 2 list the actual stockconcentrations of analyte in whole blood that were used for creating theDBS samples. Column 3 (“Reactivity”) indicates the percentage of trialsyielding positive results (i.e., HIV-1 analyte detected). Column 4(“Avg. Recovered”) indicates the averaged product of multiplying thestatic CF by the measured concentration of analyte outputted by theautomated analyzer. Column 5 (“Bias”) indicates the magnitude ofdeviation of the average recovered concentration result from the actualanalyte concentration. Column 6 (“Std Dev Log Copies”) indicates thestandard deviation among recovered results presented in column 4. Column7 (“Total Error (Westgard)”) presents results calculated in accordancewith a standard Westgard analysis protocol. Column 8 (“Total Error(RMS)”) presents results calculated in accordance with the above-citedRMS analysis protocol.

TABLE 1 Quantitative Adjustment Using a Static CF Avg. Log Recov- StdTotal Target Target ered (log Dev Error Total (copies/ (copies/ Re-copies/ Log (West- Error ml) ml) activity ml) Bias Copies gard) (RMS)900 2.95 97% 2.02 0.93 0.53 2.00 1.07 1,000 3.00 97% 2.00 1.00 0.52 2.041.13 1,200 3.08 97% 2.21 0.87 0.53 1.92 1.01

The results presented in Table 1 indicated that Total Error, regardlessof the method used for making the determination, undesirably exceededthe acceptable 1.0 threshold goal. Although not shown, differentconstant CF values substituted in place of 29.1 also gave unacceptableresults.

Example 2 presents experimental results showing that a single (i.e.,constant) CF cannot be used for quantifying analyte over the dynamicrange of the assay, particularly at lower analyte concentrations. Aswill be apparent from the results presented below, lower concentrationvalues outputted by the nucleic acid analyzer calibrated for processingplasma samples had to be multiplied by higher CFs to recover correctstarting concentrations used to prepare the DBS samples. Likewise,higher outputted values had to be multiplied by lower CFs to recovercorrect starting concentrations used to prepare the DBS samples.

Example 2 The Correction Factor is not Constant Across the Dynamic Rangeof the Quantitative Real-Time Assay

Procedures essentially described under Example 1 were followed toprepare DBS samples using whole blood spiked with different levels ofthe HIV-1 analyte. The DBS samples were processed as described above,and eluted polynucleotides amplified and detected using the Aptima HIV-1Quant Dx real-time viral load assay on the automated Panther nucleicacid analyzer (Hologic, Inc.). The target HIV-1 concentration used forDBS preparation was compared to measured concentration in the assay tocalculate the appropriate CF for each HIV-1 concentration inputaccording to equation Eq 4.

$\begin{matrix}{{CF} = \frac{{Analyte}{concentration}{in}{blood}{used}{to}{prepare}{the}{}{DBS}}{{Conc}entr{ation}{result}{measured}{by}{nucleic}{acid}{analyzer}}} & \left( {{Eq}4} \right)\end{matrix}$

TABLE 2 Correction Factor Needed for Adjustment Varies as a Function ofMeasured Target Concentration Measured Calculated Target (log TargetConc. CF copies/ml) (copies/ml) (copies/ml) (Eq 4) 2.70 500 1.1 455 2.88750 4.0 188 3.00 1,000 28 36 3.38 2,400 33 73 4.00 10,000 175 57 5.00100,000 1,546 65 6.00 1,000,000 27,347 37 6.70 5,011,872 122,119 41 7.3019,952,623 543,574 37 7.60 39,810,717 1,229,821 32

The results presented in Table 2 clearly indicated that a single, fixedor static CF value could not be used for correctly quantifyingpolynucleotide analyte over the dynamic range of the assay. The finalcolumn in the table generally reveals a trend where higher CF valueswere required for correctly quantifying samples having lowerconcentrations of the polynucleotide analyte.

Example 3 describes development of a quantitative approach using a CFvalue that varied as a function of the measured result calibrated for aliquid sample (e.g., plasma) different from the liquid sample undergoingtesting (i.e., an extracted DBS sample). This type of variable CF issometimes referred to as “non-static.”

Example 3 Development of a Non-Static Correction Factor

A total of 747 DBS samples were prepared using whole blood stocks havingdifferent known analyte HIV-1 concentrations that spanned thequantification range of the model real-time quantitative assay. Forcompleteness, the known analyte HIV-1 concentrations used for creatingthe DBS samples were the same as presented in the first column of Table2. The DBS samples were reconstituted with 1 ml of a buffered detergentsolution (i.e., DBS extraction buffer), and 500 μl of the resultingsolution was used for nucleic acid isolation and target amplificationand detection with the model real-time quantitative assay. Target (i.e.,actual) HIV-1 concentration was compared to measured concentration inthe assay to calculate the appropriate CF for each HIV-1 concentrationusing equation Eq 4. The CF multiplier required for adjusting HIV-1measured analyte concentration values to equal known input analyteconcentrations were then plotted as a function of measured copy values.The resulting data was then used for optimizing a non-linear equationaccording to standard mathematical curve-fitting techniques that will befamiliar to those having an ordinary level of skill in the art. Althoughmany different non-linear equations can be used for this purpose, thetechnique is illustrated in FIG. 1 using a fitted 4-PL equation. It willbe recognized that curve-fitting using 4-PL equations are frequentlyused for processing data exhibiting biphasic or sigmoid curveproperties.

The results presented in FIG. 1 graphically confirmed that the CF valueswere not static or constant, but instead varied as a non-linear functionof the measured concentration value outputted by the nucleic acidanalyzer calibrated for processing of plasma samples. Clusters of datapoints appearing as spaced-apart crescent-shapes demonstrate variabilityamong calculated CF results for single-level input amounts. Stateddifferently, a collection of DBS samples harboring substantially thesame amount of polynucleotide analyte (i.e., the dried blood spotshaving been prepared using a single stock of diluted analyte) naturallyyielded a range of CF values. Coefficients for the optimized 4-PLequation (i.e., Eq 1) shown as the fitted curve in FIG. 1 were asfollows: b=3.705178; c=47.21279; d=486.6657; and e=0.506889. Notably,the fact that the data in the present case did not particularly conformto a sigmoid shape did not prevent usefulness of the 4-PL equation, asdemonstrated in the following Example.

Example 4 demonstrates use of CF values determined by a fittednon-linear curve. More specifically, the determined CF value wasmultiplied by the measured quantitative result outputted from areal-time nucleic acid analyzer (measured in copies/ml) to indicate theanalyte concentration in the liquid sample used to prepare the driedblood spot.

Example 4 Correction Factor Calculated from Non-Linear Curve FitImproved Analyte Quantification

Procedures essentially described under Example 1 were followed toprepare DBS samples using whole blood spiked with different levels ofthe HIV-1 analyte. The DBS samples were processed as described above,and eluted polynucleotides amplified and detected using the Aptima HIV-1Quant Dx real-time viral load assay on the Panther automated nucleicacid analyzer. Outputted (i.e., measured) quantitative results weremultiplied by CF values taken from the fitted curve shown in FIG. 1 .More specifically, the equation for the fitted curve shown in the FIGUREwas solved to determine a CF value using the outputted quantitativeresult on the horizontal axis as the independent variable (i.e.,x-value) in the equation. The determined CF value was then multiplied bythe same outputted quantitative result (i.e., x-value) to calculate a“recovered” (i.e., adjusted) concentration. Results are presented inTable 3.

TABLE 3 Quantitative Adjustment Using a Calculated CF Target RecoveredStd Total Target (log (log Dev Error Total (copies/ copies/ Re- copies/Log (West- Error ml) ml) activity ml) Bias Copies gard) (RMS) 900 2.9597% 2.79 0.17 0.47 1.10 0.50 1,000 3.00 97% 2.78 0.22 0.46 1.15 0.511,200 3.08 97% 2.91 0.17 0.37 0.91 0.41

The results presented in Table 3 confirmed that use of the CF calculatedfrom the fitted non-linear equation substantially improved thequantitative capacity of the assay. As indicated under the final twocolumns of the table, TE values were substantially reduced when comparedwith results presented in Table 1. Stated differently, use of the CFcalculated from a fitted non-linear equation yielded significantimprovements when compared with a similar process employing a fixedvalue (i.e., CF=29.1). The LLOQ of the assay in this Example was 813copies/ml (i.e., 2.91 log copies/ml). Among all results obtained usingthree different reagent lots, the highest LLOQ determined usingcalculated CF values taken from the fitted curve shown in FIG. 1 was 883copies/ml (i.e., 2.95 log copies/ml).

Example 5

Use of Correction Factor Equation Improves Assay Precision and Accuracy

Procedures disclosed herein were used to prepare DBS samples from wholeblood stocks spiked with an HIV-1 analyte at 900 copies/ml, 1,000copies/ml, or 1,200 copies/ml. Polynucleotides eluted from the sampleswere amplified using the Aptima HIV-1 Quant DX real-time viral loadassay on the Panther automated nucleic acid analyzer. Reported resultswere obtained using procedures carried out in our own laboratories withthe intention of analyzing performance around the medically relevantdecision point of 1,000 copies/ml. Averaged results obtained using threedifferent reagent lots are presented in Table 4.

TABLE 4 Use of the CF Equation Increased Accuracy and Precision Avg.Avg. Precision Precision Log Adjusted Adjusted Std. Dev. Std. Dev.Target Target HIV log HIV log Log Log Conc Conc copies/ml copies/mlcopies/ml copies/ml (copies/ (copies/ using CF using CF for CF of for CFml) ml) of 29.1 Equation 29.1 Equation 900 2.95 2.21 2.89 0.48 0.421,000 3.00 2.18 2.91 0.49 0.32 1,200 3.08 2.38 3.01 0.46 0.27

The results presented in Table 4 show that the CF calculated from thenonlinear equation, when multiplied by the result measured in copies/mlfor a plasma sample, advantageously yielded higher accuracy inquantitative assignments with greater precision. Columns 1 and 2 in thetable indicate HIV-1 target concentrations of stock samples used tocreate the DBS samples. Columns 3 and 4 show adjusted HIV concentrationsdetermined by multiplying a CF (29.1 for column 3; calculated valueusing the equation from the fitted curve in FIG. 1 for column 4) by anoutputted result from the model viral load assay that had beencalibrated for quantifying plasma samples, and not DBS samples. Thedifference between the values presented under column 2 and the valuespresented under columns 3 and 4 reflect accuracy of assays employing thedifferent correction factor approaches. In every instance, the magnitudeof the difference was lower when the CF equation was used instead of thestatic CF. These smaller differences indicate more accuratequantification. Columns 5 and 6 show measures of precision (i.e.,standard deviations among measured concentrations for replicates).Again, in every instance the standard deviation was lower when the CFequation was used instead of the static CF. This indicated use of the CFequation was associated with greater precision in the quantitativeresults.

Example 5 presents clinical data demonstrating how improved assayquantification resulting in higher clinical sensitivity at the medicaldecision point of 1,000 copies/ml for HIV-1 was achieved by employing aCF multiplier calculated using an equation for the fitted curve shown inFIG. 1 . Notably, the data used to obtain the fitted curve was not thesame clinical data that was processed in the Example. This furtherdemonstrated how a fitted curve (or the equation therefor) could beprepared using one data set, and then used for determining CF values andprocessing a different data set (e.g., a data set obtained using adifferent instrument to perform the assay).

Example 5 Improvement in Clinical Performance at the WHO RecommendedMedical Decision Point of 1,000 Copies/Ml for HIV-1 Viral LoadMonitoring

Paired plasma and DBS specimens were collected from HIV-1 positivepatients on antiretroviral therapy. Two replicates were tested for theplasma specimen, and viral load results obtained using the proceduresdescribed herein were then averaged and used as a reference.Approximately 5 reconstituted DBS samples were also tested from eachpatient, and the measured quantitative results multiplied either by astatic CF (i.e., 29.1) or a CF calculated using the non-linear equationfor the fitted curve shown in FIG. 1 to obtain recovered concentrationvalues. Results were then compared to the plasma reference standard atthe medically relevant decision point of 1,000 copies/ml. It should benoted that 90% of results in this study had plasma viral load<10,000copies/ml, making this dataset ideal for assessment of clinicalperformance around 1,000 copies/ml of HIV.

As supported by the results presented in Tables 5 and 6, assaysensitivity at 1,000 copies/ml improved from 79.83% to 90.56% when theCF was determined from the non-linear equation compared to the staticvalue. The change from one CF value to the other did not have asignificant negative impact on specificity. This will be evident fromthe specificity of 94.30% obtained using the static CF of 29.1 versus91.36% obtained using the CF equation. The close correspondence betweenthese latter values indicated minimal impact on specificity.

TABLE 5 Results Processed Using a Static Correction Factor HIV DBS viralHIV viral load in copies/ml load in copies/ml plasma (2 replicateaverage) (CF 29.1) <1,000 >1,000 Grand Total <1,000 1,157 471,204 >1,000 70 186 256 Grand Total 1,227 233 1,460 Total Agreement91.99% Sensitivity (Pos Agreement) 79.83% Specificity (Neg Agreement)94.30%

TABLE 6 Results Processed Using a Correction Factor Calculated from aNon-Linear Equation HIV DBS viral HIV viral load in copies/ml load incopies/ml plasma (2 replicate average) (CF Equation) <1,000 >1,000 GrandTotal <1,000 1,121 22 1,143 >1,000 106 211 317 Grand Total 1,227 2331,460 Total Agreement 91.23% Sensitivity (Pos Agreement) 90.56%Specificity (Neg Agreement) 91.36%

While the present disclosure has been described and shown inconsiderable detail with reference to certain illustrative embodiments,including various combinations and sub-combinations of features, thoseskilled in the art will readily appreciate other embodiments andvariations and modifications thereof as encompassed within the scope ofthe present disclosure. Moreover, the descriptions of such embodiments,combinations, and sub-combinations is not intended to convey that thedisclosure requires features or combinations of features other thanthose expressly recited in the claims. Accordingly, the presentdisclosure is deemed to include all modifications and variationsencompassed within the spirit and scope of the following numberedembodiments.

Although various embodiments of the present disclosure have beenillustrated and described in detail, it will be readily apparent tothose skilled in the art that various modifications may be made withoutdeparting from the present disclosure or from the scope of the appendedclaims.

1. A method of quantifying a polynucleotide analyte present in a fluidblood sample that dried to produce a dried blood spot (DBS), the methodcomprising the steps of: (a) performing a nucleic acid amplificationreaction using the DBS as a source of templates to produce amplificationproducts and obtain a measured result, the measured result indicating aconcentration or an amount of the polynucleotide analyte; and (b)multiplying the measured result by a correction factor to obtain acorrected result, wherein the correction factor is the solution to anequation that specifies the correction factor as a function of themeasured result, and wherein the equation comprises a non-linearequation, thereby quantifying the polynucleotide analyte present in thefluid blood sample.
 2. A method of quantifying a polynucleotide analytepresent in a fluid blood sample that created a dried blood spot (DBS),the method comprising the steps of: (a) performing a nucleic acidamplification reaction using the DBS as a source of templates to produceamplification products and obtain a measured result, the measured resultindicating a concentration or an amount of the polynucleotide analyte;(b) solving an equation to determine a correction factor, wherein theequation specifies the correction factor as a function of the measuredresult, and wherein the equation comprises a non-linear equation; and(c) multiplying the measured result by the correction factor to obtain acorrected result, thereby quantifying the polynucleotide analyte presentin the fluid blood sample.
 3. (canceled)
 4. The method of claim 2,wherein the non-linear equation comprises coefficients optimized in amathematical curve fitting procedure to define a fitted curve.
 5. Themethod of claim 4, wherein the non-linear equation comprises fourcoefficients.
 6. The method of claim 2, wherein step (a) comprisesperforming with an automated nucleic acid analyzer that amplifies thepolynucleotide analyte and detects amplification products as the nucleicacid amplification reaction is occurring.
 7. The method of claim 6,wherein the non-linear equation in step (b) is a non-linear equationprepared using results obtained from an automated nucleic acid analyzerdifferent from the automated nucleic acid analyzer used for performingthe nucleic acid amplification reaction in step (a).
 8. The method ofclaim 2, wherein step (a) comprises performing with an automated nucleicacid analyzer that isolates the polynucleotide analyte, and thenamplifies the isolated polynucleotide analyte.
 9. The method of claim 8,wherein the automated nucleic acid analyzer further detects synthesis ofamplification products as the nucleic acid amplification reaction isoccurring.
 10. The method of claim 2, wherein the measured resultindicates a concentration of the polynucleotide analyte in a plasmasample.
 11. The method of claim 2, wherein the nucleic acidamplification reaction is an isothermal nucleic acid amplificationreaction.
 12. The method of claim 11, wherein the isothermal nucleicacid amplification reaction is a transcription-associated nucleic acidamplification reaction.
 13. The method of claim 12, wherein thetranscription-associated nucleic acid amplification reaction comprises atranscription mediated amplification (TMA) reaction.
 14. The method ofclaim 7, wherein the polynucleotide analyte comprises a segment of aviral genome.
 15. The method of claim 14, wherein the viral genomecomprises RNA.
 16. The method of claim 15, wherein the polynucleotideanalyte comprises a segment of an HIV-1 genome.
 17. The method of claim2, wherein the fluid blood sample comprises whole blood.
 18. A computerprogrammed with software instructions for quantifying a polynucleotideanalyte present in a fluid blood sample that dried to produce a driedblood spot (DBS), the software instructions, when executed by thecomputer, cause the computer to: (a) receive a measured result; (b)solve a non-linear equation to determine a correction factor, whereinthe non-linear equation specifies the correction factor as a function ofthe measured result; (c) multiply the measured result by the correctionfactor to calculate a corrected result; and (d) record the correctedresult in a non-transient form, thereby quantifying the polynucleotideanalyte.
 19. The computer of claim 18, wherein the measured result isdetermined from results of a real-time nucleic acid amplificationreaction, wherein the real-time nucleic acid amplification reaction iscarried out using the DBS as a source of templates to produceamplification products, and wherein the measured result indicates aconcentration or an amount of the polynucleotide analyte.
 20. Thecomputer of claim 19, wherein the measured result and the correctedresult are both expressed in concentration units.
 21. (canceled)
 22. Thecomputer of claim 18, wherein the non-linear equation comprisescoefficients optimized in a mathematical curve fitting procedure todefine a fitted curve.
 23. The computer of claim 22, wherein thenon-linear equation comprises four coefficients.
 24. The computer ofclaim 18, wherein the non-transient form comprises storage on acomputer-readable memory device.
 25. The computer of claim 18, whereinthe fluid blood sample comprises whole blood. 26-32. (canceled)
 33. Amethod of quantifying an analyte present in a bodily fluid sample thatdried to produce a dried sample, the method comprising the steps of: (a)performing a reaction using the dried sample as a source of analyte toobtain a measured result, the measured result indicating a concentrationor an amount of the analyte; and (b) multiplying the measured result bya correction factor to obtain a corrected result, wherein the correctionfactor is the solution to an equation that specifies the correctionfactor as a function of the measured result, and wherein the equationcomprises a non-linear equation, thereby quantifying the analyte presentin the bodily fluid sample.
 34. (canceled)
 35. The method of claim 33,wherein the non-linear equation comprises coefficients optimized in amathematical curve fitting procedure to define a fitted curve.
 36. Themethod of claim 35, wherein the non-linear equation comprises fourcoefficients.
 37. The method of claim 33, wherein the analyte is apolynucleotide analyte, and wherein step (a) comprises performing withan automated nucleic acid analyzer that amplifies the polynucleotideanalyte and detects amplification products as the nucleic acidamplification reaction is occurring.
 38. The method of claim 37, whereinthe non-linear equation in step (b) comprises coefficients optimized ina mathematical curve fitting procedure to define a fitted curve, andwherein the non-linear equation is prepared using results obtained froman automated nucleic acid analyzer different from the automated nucleicacid analyzer used for performing the nucleic acid amplificationreaction in step (a).
 39. The method of claim 37, wherein step (a)comprises performing with an automated nucleic acid analyzer thatisolates the polynucleotide analyte, and then amplifies the isolatedpolynucleotide analyte.
 40. (canceled)
 41. The method of claim 39,wherein the measured result indicates a concentration of thepolynucleotide analyte in a plasma sample.
 42. The method of claim 39,wherein the nucleic acid amplification reaction is an isothermal nucleicacid amplification reaction.
 43. The method of claim 42, wherein theisothermal nucleic acid amplification reaction is atranscription-associated nucleic acid amplification reaction.
 44. Themethod of claim 43, wherein the transcription-associated nucleic acidamplification reaction comprises a transcription mediated amplification(TMA) reaction.
 45. The method of claim 37, wherein the polynucleotideanalyte comprises a segment of a viral genome.
 46. The method of claim45, wherein the viral genome comprises RNA.
 47. The method of claim 46,wherein the polynucleotide analyte comprises a segment of an HIV-1genome.
 48. The method of claim 33, wherein the bodily fluid sample isselected from the group consisting of a whole blood sample, a plasmasample, a urine sample, and a saliva sample.